[FIXED] Add second row and assign values to them based on values of first row

Issue

I have a dataframe like this, but much larger:

    velocity  mass  volume  acceleration  temperature  pressure
0    100       4.5   12      1.3           45           6.5
1    120       5.5   15      2.1           60           7
2    130       6     11      2             55           12

I would like to add the units of measurements (UOMs) to the second row. However, the challenge I am having is that I would like to add the UOMs depending on the value of the first row, instead of hard coding them. For instance, if the first row/first column is velocity, I want the row right below it to have a UOM of 'm/s', and if it is a mass, then the UOM must be 'kg' and so on.

I was thinking perhaps it would be a good idea to create a dictionary, like: {'velocity': 'm/s', 'mass':'kg', etc} and then write a looping logic, where if the row value is the key in a dictionary, then assign the value of it.

The output df I want is as follows:

    velocity  mass  volume  acceleration  temperature  pressure
    m/s       kg    gal     m/s2          deg C        atm
0    100       4.5   12      1.3           45           6.5
1    120       5.5   15      2.1           60           7
2    130       6     11      2             55           12

Solution

I think yes you can define a dict first and go like:

uom_dict={'velocity':'m/s',
          'mass': 'kg',
          'volume':'gal',
          'acceleration': 'm/s2',
          'temperature':'deg C',
          'pressure':'atm'}

df.columns = pd.MultiIndex.from_arrays([df.columns, df.columns.map(uom_dict)])

output:

velocity    mass    volume  acceleration    temperature     pressure
    m/s     kg       gal    m/s2            deg C           atm
0   100     4.5      12     1.3             45              6.5
1   120     5.5      15     2.1             60              7.0
2   130     6.0      11     2.0             55              12.0

Answered By - SomeDude